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Tracking emissions in the US electricity system.
de Chalendar, Jacques A; Taggart, John; Benson, Sally M.
Afiliação
  • de Chalendar JA; Energy Resources Engineering, Stanford University, Stanford, CA 94305-2205; jdechalendar@stanford.edu.
  • Taggart J; Management Sciences and Engineering, Stanford University, Stanford, CA 94305.
  • Benson SM; Energy Resources Engineering, Stanford University, Stanford, CA 94305-2205.
Proc Natl Acad Sci U S A ; 116(51): 25497-25502, 2019 12 17.
Article em En | MEDLINE | ID: mdl-31792173
ABSTRACT
Understanding electricity consumption and production patterns is a necessary first step toward reducing the health and climate impacts of associated emissions. In this work, the economic input-output model is adapted to track emissions flows through electric grids and quantify the pollution embodied in electricity production, exchanges, and, ultimately, consumption for the 66 continental US Balancing Authorities (BAs). The hourly and BA-level dataset we generate and release leverages multiple publicly available datasets for the year 2016. Our analysis demonstrates the importance of considering location and temporal effects as well as electricity exchanges in estimating emissions footprints. While increasing electricity exchanges makes the integration of renewable electricity easier, importing electricity may also run counter to climate-change goals, and citizens in regions exporting electricity from high-emission-generating sources bear a disproportionate air-pollution burden. For example, 40% of the carbon emissions related to electricity consumption in California's main BA were produced in a different region. From 30 to 50% of the sulfur dioxide and nitrogen oxides released in some of the coal-heavy Rocky Mountain regions were related to electricity produced that was then exported. Whether for policymakers designing energy efficiency and renewable programs, regulators enforcing emissions standards, or large electricity consumers greening their supply, greater resolution is needed for electric-sector emissions indices to evaluate progress against current and future goals.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article